Aspect-based sentiment analysis includes the machine processing of text to determine aspects (e.g., topics) that the text refers to, as well as a sentiment conveyed for aspects. Aspect extraction is an important and challenging task in aspect-based sentiment analysis. Attention-based long short-term memory (LSTM) networks have proven to be useful in aspect-level sentiment classification. However, due to the difficulties in annotating aspect-level data, existing public datasets for this task are all relatively small, which largely limits the effectiveness of those neural models.